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Webinterface

This component let's the user register terms for analyzing.

Webinterface Screenshot

Build and Deploy

  • Login to your account to dockerhub: docker login
  • From the root of this project, build a new docker image with the respective version: docker build -t tweetsentimentanalysis/webinterface:0.0.2 -t tweetsentimentanalysis/webinterface:latest .
  • Run docker push tweetsentimentanalysis/webinterface:0.0.2 to deploy to dockerhub

Get the container

If you do not want to build the container by your own, you may use the following to get the image from DockerHub: docker pull tweetsentimentanalysis/webinterface:latest

Run the container

After you have built the container, you may run it using the following command:

docker run -p 9000:8080 -e REGISTRAR_URL='http://someUrl.toRegistrar.com' -e ELASTICSEARCH_URL='https://some.Url.com' -e AWS_ACCESS_KEY_ID="..." -e AWS_ACCESS_KEY_SECRET="..." tweetsentimentanalysis/webinterface:latest

Use the appropriate URLs as well as AWS credentials with at least the permissions of AmazonSQSReadOnlyAccess, CloudWatchReadOnlyAccesse. Note, that you also may specify the following environment variables during startup:

  • AWS_EC2_REGION: The region in which the instances of the autoscaling groups are located, e.g. us-west-2
  • AWS_ANALYZER_AUTO_SCALING_GROUP_NAME: The AWS autoscaling group name of the instances on which tweets get analyzed
  • AWS_PRODUCER_AUTO_SCALING_GROUP_NAME: The AWS autoscaling group name of the instances on which the tweets are pushed to Elasticsearch
  • AWS_FETCHED_TWEETS_SQS_QUEUE_NAME: The AWS SQS Queue name in which the fetched tweets are located
  • AWS_ANALYZED_TWEETS_SQS_QUEUE_NAME: The AWS SQS Queue name in which the analyzed tweets are located

Remove built images

In order to clean up, you may want to remove the previously created image and container:

  • Run docker ps -a in order list created containers.
  • Choose the corresponding container id and invoke docker stop <ID> && docker rm <ID>
  • Run docker images to list all created images
  • Run docker rmi <ID> with the id of the image to remove it